Multi‐sensor and Multi‐model Monitoring and Investigation of a Wintertime Air Pollution Event Ahead of a Cold Front over Eastern China,Journal of Geophysical Research: Atmospheres

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Multi‐sensor and Multi‐model Monitoring and Investigation of a Wintertime Air Pollution Event Ahead of a Cold Front over Eastern China
Journal of Geophysical Research: Atmospheres ( IF 3.8 ) Pub Date : 2021-05-07 , DOI: 10.1029/2020jd033538
Xiao‐Ming Hu ₁ , Jun Hu _{1,

2} , Lan Gao ₃ , Changjie Cai ₄ , Yujun Jiang ₅ , Ming Xue ₁ , Tianliang Zhao ₂ , Sean M. R. Crowell ₆

Affiliation

Given the limitations in pollutant measurements (e.g., coverage, observation errors) and air quality model uncertainties (e.g., with parameterizations and emissions), a multi‐sensor and multi‐model approach offers additional benefits compared to a single‐instrument and deterministic approach for monitoring, investigating, and predicting air pollution events. In this study, we use multi‐sensors (including the spaceborne MODIS, OCO‐2, AIRS, and OMPS instruments as well as surface instruments) and multi‐models (including WRF‐Chem and WRF‐CO₂) to investigate a severe air pollution event on December 9, 2016 over eastern China. During this episode, a strong cold front moved southward. At the leading edge of the front, WRF‐CO₂ simulates an enhanced XCO₂ belt while WRF‐Chem simulates a belt of high PM_2.5 concentration. The XCO₂ and PM_2.5 belts are generally co‐located, due to co‐emission of CO₂ and pollutants (or their precursors). Satellite observations including MODIS AOD, OCO‐2 XCO₂, OMPS NO₂, AIRS CO and surface data confirm the simulated pollution and XCO₂ belts. Later on, the front became distorted due to terrain blocking and mountain channel flows. Both observations and simulations show that the channel winds between Mountains Dabie and Huang transport the haze plume into Jiangxi Province, enhancing pollution in the region. It is concluded that the multi‐sensor (including space‐ and ground‐based instruments) and multi‐model (e.g., WRF‐CO₂, WRF‐Chem) approach can be used to collectively monitor and investigate air pollution events, given that emissions of the involved species have generally similar spatial distributions.

更新日期：2021-05-07

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